It isn’t hard to encounter sentiment about the dangers of using artificial intelligence in education, almost always in the context of a potential diminishing of cognitive skills of some sort.
I tend to have a different view, which is that people show a Bell curve (a normal distribution) of intelligence or cognitive capabilities.
It follows that there would be a Bell Curve of ability to use language models in ways that enhance, rather than diminish, cognitive skills.
That might be true even when there are other forms of “intelligence” beyond those measured by intelligence quotient tests such as:
Linguistic: Skill with words and language.
Logical-Mathematical: Skill with numbers and logic.
Musical: Skill with pitch, rhythm, and sound.
Bodily-Kinesthetic: Skill with body movement and control.
Visual-Spatial: Skill with visual spaces and pictures.
Interpersonal: Skill in understanding other people.
Intrapersonal: Skill in understanding yourself.
Naturalist: Skill in understanding nature and animals.
Existential: Skill in pondering deep questions about life.
In other words, AI can be either a cognitive substitute or a cognitive accelerator, depending on how it is used. And since human cognition and curiosity arguably also are a Bell Curve, some are almost naturally going to use it better than others.
For example, one review examined 67 studies on critical thinking and use of ChatGPT found that ChatGPT supports cognitive development in some instances, while declines in creativity and critical thinking happened in other instances.
A possibly-oversimplified view is that how much thinking a learner did before conducting research (asking questions) and after doing that research seemingly matters.
When learners used ChatGPT for “cognitive offloading (replacing thinking), both creativity and critical thinking seemed to suffer.
In other words, it is “how you use it” that matters. For example, if primarily used for summarization and writing (“Cliff Notes” or essay writing), critical thinking skills were not enhanced.
If learners essentially substituted ChatGPT for their own thinking and questioning, cognitive skills arguably were not enhanced.
The point is that, in an earlier form, calculator use diminished the amount of arithmetic humans needed to perform.
But such use can increase the amount and sophistication of mathematics they can do, provided they still understand the underlying mathematics.
Use of calculators did not automatically decrease math skills. Such use shifted the potential terrain. And there is arguably a Bell curve of ability, willingness and skill in doing so.
In the same way, using language models poses some reduction of skills or effort:
memory retrieval
mental calculation
information search skills
initial formulation
sustained attention
epistemic vigilance
argument construction.
But that doesn't necessarily mean that overall intellectual capability falls. AI potentially creates new possibilities which might be grasped. Does it eliminate a cognitive activity or only a bottleneck to more valuable cognitive activities?
And much of the answer will depend on the learners themselves.
Granted, much of my own work involves research. And it turns out that language models are very helpful for research.
When doing any sort of research with a historical component (what happened, when, by whom, with what results or patterns), an idealized pre-language-model process might look like:
search Google
search Wikipedia
find books and articles
search companies
follow references
discover competing interpretations
figure out terminology
search more
construct a mental map
begin asking other questions.
Language models reduce the time required for the first eight activities, generally speaking, even when simpler questions, well within an existing domain, and not requiring all those steps, are tackled.
So the research reached the latter two stages much faster.
The caveat is that the ability to comprehend and recall is more important inside structured learning processes (“education”) where "learning" means the ability to recall a specific body of information. “There will be a test,” in other words.
The ability to synthesize and extrapolate arguably is more important outside such structured learning situations (work, innovation, discovery).
The implication is that different people are going to use language models, in formal education, in better or less good ways. No single set of guardrails or exhortations is going to change that.
Much still relies, as it does almost everywhere in life, with the motivation and aptitude of the user.
